Ghayur et al., Equity Smart Beta and Factor Investing for Practitioners

Equity Smart Beta and Factor Investing for Practitioners by Khalid Ghayur, Ronan G. Heaney, and Stephen C. Platt (Wiley, 2019) is, according to the publisher, the first full-length book on these topics, although scores of papers have been published on smart beta and equity factors. The named authors are all on the Goldman Sachs Alternative Investment Strategies team within its Asset Management’s Quantitative Investment Strategies platform. Several academics and practitioners contributed chapters to this more than 450-page volume, especially in the parts dealing with asset owner perspectives, consultant perspectives, and retail perspectives.

Retail investors are unlikely to profit from this detailed book since, if they commit a portion of their portfolios to smart beta, they will most likely do so through exchange-traded products. As of June 2017, they would have had a choice of 1,320 ETPS and could have paid fees close to those charged by passive funds.

This book is primarily addressed to institutional investors, fund managers, and wealth managers. It covers the field of smart beta investing with the thoroughness one would expect of a Goldman Sachs team, and it answers questions investors and managers (and their clients) might have—and I’m sure many others that never crossed their minds. For instance, it explains smart beta factor return premia, describes weighting schemes and factor specifications, decomposes the risk of smart beta strategies, looks at the performance characteristics both of individual smart beta factors and of factor diversification strategies, and analyzes how to combine smart beta with smart alpha as well as how to incorporate ESG with smart beta.

At the end of the book the authors respond briefly to skepticism about smart beta investing—e.g., that factors are data mined, that some factors are inconsistent with theory, that smart beta is just active management rebranded and repackaged, that factors can’t persist in efficient markets, and that factor persistence will be challenged by crowding.

Colonna, Reboot

Wired Magazine called Jerry Colonna, the venture capitalist turned executive coach, “the CEO whisperer.” In Reboot: Leadership and the Art of Growing Up (Harper Business/HarperCollins, 2019) Colonna essentially whispers to himself and to the reader, illustrating and encouraging radical self-inquiry.

The book is nothing like the usual business fare. It is more self-therapy for business leaders who, Colonna contends, can truly lead only if they make peace with their own inner demons. It has such chapter titles as “Standing Still in Empty Time” and “Loving the Crow.”

Colonna bares his own soul in this book. He describes the extreme difficulties he experienced growing up with an alcoholic father and a mentally ill mother and how these difficulties became the baggage he carried with him wherever he went, including to a mental hospital to which he was committed when he was a teenager, and throughout his successful careers. But, he believes, by confronting our baggage and rebooting ourselves, we can become the leaders we were meant to be.

I think the best way to give a sense of this book is to quote its final paragraph in full:

“I will always be haunted by lemon drops, sawdust, and the power of words. I am grateful this is so. Out of such pain, such suffering, and the muck and mud of my ocean bottom, a tall, strong tree of a man has emerged. I overcame the wordlessness of my youth. I became a good man by learning to love words—first, those of others; then, later my own words. I became who I was born to be by learning to read and then, later, to write. I learned that a life well written is a life well led. I became a good leader and I’m still becoming a good man. That is my legacy: the wisdom of knowing that the act of becoming a good man is more important than arriving at that place. With that, I’ve begun mastering the art of growing up.”

I must admit that Reboot does not speak to me, but that may say more about me than about the book.

Lebron, The Laws of Trading

Augustin Lebron, formerly a trader and researcher at Jane Street Capital and now head of a consulting firm on decision-making, has written a refreshingly cerebral book, The Laws of Trading: A Trader’s Guide to Better Decision-making for Everyone (Wiley, 2019). Although the book’s pitch is that “mental tools, forged in the competitive fire of financial markets, help us make good decisions in all other areas of life,” the book is first and foremost about the principles underlying sophisticated, professional trading. A reader who knows nothing about the financial markets, the “everyone” of the subtitle, would be lost in the thicket of options models and hedge optimization. On the other hand, a trader who picks up this book will be drawn into a fascinating meta-analysis of the tools he does or should use and will probably have little interest in applying them to the world outside of trading. This is not a criticism of the book, just of its marketing.

The book is, in fact, terrific. In eleven chapters it covers motivation, adverse selection, risk, liquidity, edge, models, costs and capacity, possibility, alignment, technology, and adaptation.

Take the ever-vexing issue of edge. Lebron sets out the fundamental axiom of edge: “all trades that have edge are profitable because there is some fact about the world that you understand and can act on that the marginal participant in the market doesn’t understand or can’t act on.” The marginal trader is the only one who matters, and he is (if you’re the buyer) “the most aggressive seller who isn’t aggressive enough to hit a bid himself.” So, to do profitable trading, you don’t need to be the best, just better than the trader of the median share. Alas, that trader is both sophisticated and skilled. “In any mature market, the really bad traders have either left or trade very small, and good traders (ones with edge) are everywhere, because they’re the ones that survived.”

What kinds of models should traders build? Should they be “descriptive of a true underlying structure of the world (a generative model)” or is “describing some observed regularity (a phenomenological model)” good enough? Both kinds of models are scary. With generative models, it is all to easy to mistake the map for the territory. With phenomenological models, it’s very difficult to know when the perceived regularity will stop existing.

Lebron also addresses the role of the inductive hypothesis (that if one has seen some regularity in the past, it makes sense that it should continue in the future) in financial markets. Because markets are both stochastic and self-organized feedback systems, relying on the inductive hypothesis is problematic. Which leads to the rule: “Just because something has never happened doesn’t mean it can’t. Corollary: Enough people relying on something being true makes it false.”

The Laws of Trading is, to my mind, essential reading for traders who want not only to survive but to flourish. It certainly won’t guarantee success (or continued success), but it will prompt the trader to reflect on his biases and perhaps even his ignorance. And it will provide him with new ways to think about framing trades.